TY - GEN

T1 - Bayesian model updating for existing seismi-isolated bridges using observed acceleration response data

AU - Kitahara, Masaru

AU - Broggi, Matteo

AU - Beer, Michael

N1 - Conference code: 11

PY - 2020

Y1 - 2020

N2 - In ageing existing bridges, the deterioration of the members cannot be ignored and the model parameters should be carefully estimated in time through observation data from the structures. On seismic-isolated bridges, the post-yield stiffness of rubber bearings is a particularly critical parameter, since it affects the structural behavior against huge earthquakes. Additionally, its characteristic can be captured using available seismic response data. In this study, a seismic-isolated bridge pier is modelled as a two degree of freedom lumped mass system and its uncertain model parameters are estimated based on time-histories of the acceleration response through Bayesian model updating. The Bhattacharyya distance is used as a comprehensive uncertainty quantification (UQ) metric to capture multiple uncertainty sources from both model predictions and observation data. A sequential procedure is proposed to prevent the so-called "dimensional curse " due to very high dimensional time-series data in model updating. In this procedure, the Bhattacharyya distance is calculated for each predefined time segment and their root mean square is adopted as the UQ metric. The results demonstrate that the proposed framework can successfully update model parameters including the post-yield stiffness of the rubber bearing through seismic response data. Furthermore, the calibrated model can represent wholly the probability distribution of the target time-series observation.

AB - In ageing existing bridges, the deterioration of the members cannot be ignored and the model parameters should be carefully estimated in time through observation data from the structures. On seismic-isolated bridges, the post-yield stiffness of rubber bearings is a particularly critical parameter, since it affects the structural behavior against huge earthquakes. Additionally, its characteristic can be captured using available seismic response data. In this study, a seismic-isolated bridge pier is modelled as a two degree of freedom lumped mass system and its uncertain model parameters are estimated based on time-histories of the acceleration response through Bayesian model updating. The Bhattacharyya distance is used as a comprehensive uncertainty quantification (UQ) metric to capture multiple uncertainty sources from both model predictions and observation data. A sequential procedure is proposed to prevent the so-called "dimensional curse " due to very high dimensional time-series data in model updating. In this procedure, the Bhattacharyya distance is calculated for each predefined time segment and their root mean square is adopted as the UQ metric. The results demonstrate that the proposed framework can successfully update model parameters including the post-yield stiffness of the rubber bearing through seismic response data. Furthermore, the calibrated model can represent wholly the probability distribution of the target time-series observation.

KW - Ageing existing bridge

KW - Bayesian model updating

KW - Bhattacharyya distance

KW - Time-series data

KW - Uncertainty quantification

UR - http://www.scopus.com/inward/record.url?scp=85098722849&partnerID=8YFLogxK

U2 - 10.47964/1120.9291.18937

DO - 10.47964/1120.9291.18937

M3 - Conference contribution

AN - SCOPUS:85098722849

SP - 3558

EP - 3566

BT - EURODYN 2020

A2 - Papadrakakis, Manolis

A2 - Fragiadakis, Michalis

A2 - Papadimitriou, Costas

T2 - 11th International Conference on Structural Dynamics, EURODYN 2020

Y2 - 23 November 2020 through 26 November 2020

ER -